Bertis Joins the Ministry of Science and ICT’s ‘Development of Technologies for Spatial Proteomics-Based Multi-Omics Analysis’ Project

-    6 institutions participate with a total research budget of approximately 9 billion KRW over 4 years and 6 months

-   Bertis participates in securing global-level spatial proteomics technologies with its expertise in proteomics-based biomarkers

On September 6, Bertis, a company specializing in the development of proteomics-based precision medicine technology (led by CEOs Dong-young Noh and Seung-man Han), announced its participation as a research institution in the ‘Development of Materials and Component Technologies for Spatial Proteomics-Based Multi-Omics Analysis’ project (Project No. RS-2024-00454407), led by the Ministry of Science and ICT and the National Research Foundation of Korea.

This project is part of the ‘2024 Nano and Materials Technology Development Project’ initiated by the Ministry of Science and ICT and the National Research Foundation of Korea. It aims to secure global-level technologies that will drive the creation of new industries and advance key sectors, while also expanding research infrastructure and promoting commercialization.

Bertis will collaborate with the institution in charge of research, University of Ulsan College of Medicine, Meteor Biotech, Korea Animal Model Archive, Future Medicine Research Institute of CHA Bundang Medical Center of CHA University, and the Korea Basic Science Institute to form the 'Spatial Proteomics Technology Development Research Consortium.' The consortium will undertake the project to develop spatial proteomics technologies for multi-omics, with a total research budget of 9 billion KRW, until December 2028.

Spatial proteomics technology is a field that studies the spatial distribution and interactions of proteins within tissues. No commercialized technologies for spatial proteomics analysis exist, and single-cell preprocessing methods are being used as alternatives. This project will develop novel materials and foundational technologies for protein digestion, which are currently unavailable in spatial proteomics processes. The goal is to establish the first global analysis platform, from tissue separation to diagnosis, build databases, develop AI software, and create biomarkers for various cancers.

Bertis, recognized for its technological prowess in developing and utilizing proteomics-based biomarkers, will be responsible for establishing LC-MS analysis conditions using single-cells, developing spatial proteomics-specific preprocessing materials and POC (Proof of Concept), creating quality control software for fragmented tissue proteomics analysis platforms, and developing and training AI algorithms through pathology image analysis.

Kyunggon Kim, a professor in the Department of Digital Medicine at the University of Ulsan College of Medicine, head of the institution in charge of research, stated, "Spatial multi-omics is increasingly recognized as a key platform for translational research and new drug development. However, spatial proteomics is a field that demands advanced technology and material development. We are excited to collaborate with outstanding government-funded research institutions, hospitals, and companies with core technologies, such as Bertis and Meteor Biotech to conduct challenging research.”

Un-beom Kang, Head of Bertis Biomarker Research Institute and co-leader of the research, explained, “The field of proteomics has high technological utility and remarkable growth within the biotech industry, accompanied by intense global competition to secure technological superiority and foundational technologies for disease diagnosis and treatment. As a leader in the proteomics industry with expertise in commercializing technology and applying AI, Bertis is dedicated to achieving significant results in the development of spatial proteomics technologies through collaboration with leading domestic research institutions."

Meanwhile, Bertis has established its proprietary analysis system for single-cell proteomics research and is accelerating the advancement of proteomics-based precision medicine technologies by utilizing AI. The company is enhancing the accuracy of early diagnostic solutions for breast cancer, pancreatic cancer, and ovarian cancer through machine learning-based algorithms. It is also developing the SAN (Spectrum is All you Need) model, which uses large language models (LLM) to analyze protein distribution data and extract health information related to the presence or absence of target diseases.